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Parquet and Arrow: why columnar formats make your queries 100x faster
Large analytical datasets often start life as CSV files. They are easy to create, easy to open, and supported almost everywhere.
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From pickle to production: wrapping a model in a real API that won’t fall over
Training a machine learning model is only half the job. The other half is making it available reliably, safely, and predictably.
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Topics Everyone Is Talking About No390
Building an API Client for a Smart Water-Cooled Bed • Whos Afraid of Chinese AI Models? • Minimal Git CI Powered by Hooks • Chinas Open-Weight AI Strategy Gains the Edge • Hacker Erases Romanias Land Registry Database…
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Linear regression is not boring: assumptions, diagnostics, and when it beats deep learning
If you’ve been around machine learning for a while, you’ve probably seen linear regression dismissed as the “hello world” of ML. That sells it short.
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First hour with a new dataset: a repeatable EDA checklist in pandas
A new dataset is not a blank canvas. It is the result of a pipeline: databases, APIs, spreadsheets, sensors, human input, and business processes. Every one of those sources can introduce problems.
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A neuron is just a weighted sum: build a perceptron in 20 lines of NumPy
Modern AI systems can contain billions of parameters, but the core idea behind a neural network starts with a much smaller building block.
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Topics Everyone Is Talking About No387
Lone Lisp: Matheus Moreira on Building Lisp from the Linux Syscall Layer • Haskell in Production at H-E-B: Lessons from Enterprise Development • Kaiser Nurses Raise Concerns Over AI and Workplace Surveillance • Fifteen Years Later: How Hacker News Helped Build Recurse Center • Lobste.rs Successfully Migrates from MariaDB to SQLite…